Abstract
With the application of big data in Earth observation, satellite imagery data are gradually becoming important means of observation for monitoring changes in vegetation, water bodies, and urbanization. Therefore, new satellite imagery data organization and management paradigms are urgently needed to fully mine the useful information from these data and provide new ways to better quantify and serve the sustainable development of resources and the environment. In this paper, a framework for processing and analyzing Chinese GF-1 satellite imagery data was developed using the latest technologies such as Open Data Cube (ODC) grids, Analysis Ready Data (ARD) generation, and space subdivision, which extended the data loading and processing capacities of the ODC grids for Chinese satellite imagery data. Using the proposed framework, we conducted a case study to investigate the spatial and temporal changes in vegetation and water mapping with GF-1 data collected from 2014 to 2021 covering the Miyun Reservoir, Beijing, China. The experimental results showed that the proposed framework had significantly improved temporal and spatial efficiency compared with the traditional scene-based data management approach, thus demonstrating the advantages and potential of the ODC grids as a new data management paradigm.
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